TY - JOUR
T1 - How to Apply What You Learn—Research on Major-Job Matching of Higher Vocational Students
AU - Liu, Jiaqi
AU - Cai, Meng
N1 - Publisher Copyright:
© 2026 John Wiley & Sons Ltd.
PY - 2026/9
Y1 - 2026/9
N2 - An increasing number of countries recognize the significance of vocational education due to its potential to alleviate poverty and enhance the quality of life. However, major-job mismatch among Chinese vocational graduates seriously hinders the benefits of vocational education. Within the framework of Ecological Systems Theory, this study analysed data from Chinese higher vocational students and used feature selection models, such as random forest and LASSO regression, to identify key predictors of major-job matching. Binomial logit regression was then employed to conduct a comprehensive analysis and test the results' robustness. We found that internship-related factors were most strongly associated with major-job matching among higher vocational students, while intergenerational closure factors were also relatively important. Nonetheless, other factors like family socioeconomic status, which have been linked to employment quality in other studies, exhibited a weaker correlation with major-job matching for higher vocational students. This study offers insight to address the major-job mismatch faced by Chinese vocational college students, while also providing international empirical support for the ecological approach in exploring the multifaceted factors.
AB - An increasing number of countries recognize the significance of vocational education due to its potential to alleviate poverty and enhance the quality of life. However, major-job mismatch among Chinese vocational graduates seriously hinders the benefits of vocational education. Within the framework of Ecological Systems Theory, this study analysed data from Chinese higher vocational students and used feature selection models, such as random forest and LASSO regression, to identify key predictors of major-job matching. Binomial logit regression was then employed to conduct a comprehensive analysis and test the results' robustness. We found that internship-related factors were most strongly associated with major-job matching among higher vocational students, while intergenerational closure factors were also relatively important. Nonetheless, other factors like family socioeconomic status, which have been linked to employment quality in other studies, exhibited a weaker correlation with major-job matching for higher vocational students. This study offers insight to address the major-job mismatch faced by Chinese vocational college students, while also providing international empirical support for the ecological approach in exploring the multifaceted factors.
KW - ecological systems theory
KW - feature selection model
KW - higher vocational college student
KW - machine learning method
KW - major-job matching
UR - https://www.scopus.com/pages/publications/105041153051
U2 - 10.1111/ejed.70706
DO - 10.1111/ejed.70706
M3 - 文章
AN - SCOPUS:105041153051
SN - 0141-8211
VL - 61
JO - European Journal of Education
JF - European Journal of Education
IS - 3
M1 - e70706
ER -